Amdahl's law is named after computer architect Gene Amdahl, and is used to find the expected improvement to an overall system when only part of the system is improved. It is often used in parallel computing to predict the theoretical maximum speedup using multiple processors of a computing system. Amdahl's law is a model for the relationship between the expected speedup of parallelized implementations of an algorithm relative to the serial algorithm, under the assumption that the problem size remains the same when parallelized.
It has been argued that the speedup of a program using multiple processors in parallel computing is limited by the time needed for the sequential fraction of the program. Namely, “the effort expended on achieving high parallel processing rates is wasted unless it is accompanied by achievements in sequential processing rates of very nearly the same magnitude.”
However, there can be better methods of predicting speedup than Amdahl's law which predicts that the maximum parallel speedup is linear and is dominated by serialism.